Introduction
In statistical test, the test of association is widely used in order to analyse the two variables are correlated or not. The test of association is hereby used for analysing interlink between the variables, where for example, scatter plots and hypothesis testing are possible to conducted to draw final conclusions. It is playing a crucial role in data analysis, where the researchers try to conduct dissertation or thesis paper. In data analysis and evaluation, it is possible to perform test of association in order to identify the impacts of independent variables on the dependent variable in the data set. It also helps in testing the alternative and null hypothesis. The bivariate association test in this regard involves one independent variables and one dependent variable. And the researchers also can test multivariate association where there are two or more independent variables giving its impacts on the dependent variables.
Chi-Square test as an association test
Commonly, the researchers use different tests for association such as chi square test for association that is mainly used to find a relationship between two categorical variables, as well as association, the test can be used to demonstrate non-association as well. Additionally, Cochran Mantel Haenszel test is also utilised for analysing the data in thesis paper along with Fisher’s exact test is used alternative to Chi square when the researchers have small sample size. The gamma coefficient also tells how closely two pairs of data points. Goodman Kruska’s Gamma is a test for ranked variables that are also utilised for evaluating the test of association. Hereby, there are different test, through which the researchers can perform the test of association in the dissertation or thesis paper.
Mostly, Chi Square test is used for conducting test of association. A chi-squared test is written as χ² test, which is a statistical hypothesis test valid to perform when the test statistic is chi-squared distributed, under the null hypothesis, specifically Pearson's chi-squared test.
The formula of chi square is,
Where,
X2 is chi square
Oi is observed value
Ei is expected value
Chi square test for independence indicates comparison between two variables in contingency tables to see they are related or not. Hence, the researchers can utilise this for identifying the level of association between the variables in a specific data set. Hence, through this chi square test, it is possible to analyse the distribution of the categorical variables that differs from each other. The purpose of chi-square test is to determine the differences between the observed data and the expected data through it is possible for the researchers to identify the relationship between the existing variables. It further helps in testing the hypothesis developed in the dissertation or thesis papers. Comparing observed results with expected results is also helpful for further SPSS data analysis and evaluation. Goodness of fit as well as standard variance in the sample through normal distribution is also possible to be measured through Chi square test, where the researchers can identify interlink between the categorical values. Particular population standard deviation is also measured through such test for further critical evaluation.
Applications of association test
Measures of association tests are used in various fields of research but are especially common in the areas of epidemiology and psychology, where they frequently are used to quantify relationships between exposures and diseases or behaviours. The alternative and null hypothesis are tested through the test of association, where the correlation and regressions can be measured as well for identify the association between the variables in a specific population sample. Hereby, it plays a crucial role in conducting dissertation or thesis paper, where the impacts of one variable to another variable can be evaluated critically. The data analysts are utilising implicit association test widely in different researches and thesis papers. It is utilised diverse research fields, including market research, health and wellbeing, business, education and others for analysing the impacts of different variables. The association between two variables can be identified by the data analysts where they can evaluate current trend in the market as well as predict future activities. On the other hand, the data analytics are trying to test the hypothesis developed in the research for better interpretation, so that the data findings and information can be analysed critically through SPSS help.
Conclusion
Hereby, test of association is beneficial for the data analysts to progress in the research and gather vast data and authentic information to perform the test of association. The data analysts are experienced enough to sort the gathered data in a systematic way and identify the variables with different name and coding. Chi Square test is widely used for conducting test of association, in which the data analysts can draw the final conclusion through data interpretation and evaluation of the results. Hence, test of association provides a scope to evaluate the collected data and information where the data analysts are able to identify the internal link between the variables for testing the hypothesis of the paper and meeting the ultimate research objective.
